Grantee Research Project Results
2023 Progress Report: Building Community Resilience to Natural-disaster-Driven Contaminant Exposures Through System-level Risk Analysis, Management, and Readiness
EPA Grant Number: R840041Title: Building Community Resilience to Natural-disaster-Driven Contaminant Exposures Through System-level Risk Analysis, Management, and Readiness
Investigators: Borsuk, Mark E. , Wilson, Sacoby M. , Hendricks, Marccus , Calder, Ryan
Institution: Duke University , University of Maryland - College Park , Virginia Polytechnic Institute and State University
EPA Project Officer: Aja, Hayley
Project Period: August 1, 2020 through July 31, 2023 (Extended to July 31, 2024)
Project Period Covered by this Report: August 1, 2022 through July 31,2023
Project Amount: $799,756
RFA: Contaminated Sites, Natural Disasters, Changing Environmental Conditions and Vulnerable Communities: Research to Build Resilience (2019) RFA Text | Recipients Lists
Research Category: Sustainable and Healthy Communities , Safer Chemicals
Objective:
1. To develop a generalizable and comprehensive risk analysis framework that links natural hazards and changing environmental conditions to the release, fate, and transport of contaminants.
2. To collaborate with community partners to identify factors that may modify exposure and vulnerability of certain populations and include such factors in our framework to holistically assess health risks.
3. To assist communities in translating scientific products into realistic and relevant management and readiness plans that promote community resilience to natural hazards.
Progress Summary:
After Covid-related delays in Year 1, we made good progress on Objectives 1 and 2 in Years 2 and 3. However, we remain approximately 12 months behind schedule due to the initial delays. Therefore, have requested (and received) a No-Cost Extension to continue work through 07/31/2024.
We have five major outputs to report from Year 3:
- We completed and submitted a manuscript to Nature Scientific Data that describes our original dataset of above-ground storage tanks (ASTs) across the contiguous United States developed from high-resolution aerial imagery. This dataset is broadly useful for the purposes of large-scale risk and hazard assessment, production and capacity estimation, and infrastructure evaluation and is being made publicly available. It also serves as training data for our project’s automated object detection model.
- We also completed our machine-learning (ML) model for detection and classification of ASTs and are writing up a manuscript for submission to a journal. This model uses state-of-the-art neural network algorithms to automate the process of locating and classifying ASTs from high-resolution aerial imagery. These geospatial data are currently being used for our AST risk assessments.
- We are completing a systematic analysis of the risk posed by storm surge and flooding hazards to above-ground petroleum storage tanks. This involves the application of large-scale simulations of parametric logistic fragility models, structured as a Bayesian network, to make probabilistic predictions of tank failures across the US. The goal is to produce a generalizable framework for tank risk assessment available to a diversity of stakeholders.
- For the next step in our model building, we are developing a suite of Python modules to link multiple existing models to simulate the fate and transport of contaminants potentially released by simulated above-ground tanks failures.
We implemented a survey of the populations of our two partner communities to better quantify key contributors and social vulnerability to potential contaminant exposure resulting above-ground storage tank failure.
Future Activities:
In Year 3 of the project, our emphasis will be on linking the AST data set with the fragility, fate, and transport models produce an integrative graphical Bayesian network of disaster and contaminant transport events. This network will then be connected to a separate exposure and vulnerability model currently under development with input received from our community survey. The results will be used in collaboration with communities to create toolkits for developing NaTech disaster readiness and response plans.
Journal Articles:
No journal articles submitted with this report: View all 4 publications for this projectSupplemental Keywords:
Community-engaged research; total environment; sustainable and healthy communities; environmental justice; community readiness and resilience
Relevant Websites:
Professor Mark Borsuk Lab Exit
MODELS FOR ENVIRONMENTAL HEALTH AND POLICY Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.